The use of computers and mechanized systems allow for the collection of vast amounts of data. Real-world decision making often is, or should be, based upon the analysis of large volumes of data. However, much of the data that is collected or otherwise available may never be analyzed. This is so because current approaches for analyzing data are often expensive, time consuming, and require highly trained analysts or complicated tools. Less expensive approaches, such as spreadsheets and graphs, may be helpful in analyzing small amounts of data, but are not well suited in accommodating large data sets in a clear and meaningful manner. Thus, it would be advantageous to provide improved approaches for analyzing large data sets.